This series is aimed at programming language aficionados. There's a lot of very abstract writing about programming languages and a lot of simple minded "language X sux!" style blog posts by people who know next to nothing about programming. What I feel is sorely missing is a kind of article that deliberately sacrifices the last 10% of precision that make the theoretical articles dry and long winded but still makes a point and discusses the various trade offs involved. This series is meant to fill that void and hopefully start a lot of discussions that are more enlightening than the articles themselves. I will point out some parallels in different parts of computing that I haven't seen mentioned as well as analyze some well known rules of thumb and link to interesting blogs and articles.

Stupid observation you probably already know: while a lot of Math and Physics researchers usually do a lot of programming, and often become fairly well-versed in one language or another, it usually isn't C. Fortran is common, and you see your Perl users and Python users, and Ada, for people doing government work. It's not really surprising that someone who's in some other, non-CS field wouldn't be good with C, or other curly-bracket languages.